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An intiutionistic fuzzy multi-expert and multi-criteria system for effective performance management

    Ahmet Beskese Affiliation
    ; Cengiz Kahraman Affiliation
    ; Shirli Ender Buyukbay Affiliation
    ; Faik Tunc Bozbura Affiliation

Abstract

Organizations, in their pursuit of accomplishing their vision and goals, need effective management of human resources. Performance Management, among other Human Resources Management (HRM) practices, is the central function, as it delivers the necessary data that complements and enables the other functions. Building an effective performance management system is a multicriteria problem that requires contribution from experts having diverse backgrounds. Moreover, performance management is an inherently vague concept since almost the whole process requires linguistic assessments rather than numerical ones. Hence, to handle all those issues, an intuitionistic fuzzy multi-criteria and multi-expert analytical hierarchy process (AHP) based management model is proposed in this paper. In the determination of the criteria weights of the model, both the aggregated and compromised assessments of the experts are used in order to observe the effects of these two methods on the results. A numerical application is given to illustrate the use of the model.

Keyword : aggregated group decisions, compromised decisions, analytical hierarchy process (AHP), human resources management (HRM), intuitionistic fuzzy sets, performance management

How to Cite
Beskese, A., Kahraman, C., Ender Buyukbay, S., & Bozbura, F. T. (2018). An intiutionistic fuzzy multi-expert and multi-criteria system for effective performance management. Technological and Economic Development of Economy, 24(6), 2179-2201. https://doi.org/10.3846/tede.2018.6462
Published in Issue
Nov 21, 2018
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This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Aguinis, H. (2009). Performance management (2nd ed.). Upper Saddle River, NJ: Pearson Prentice Hall.

Aguinis, H., Joo, H., & Gottfredson, R. K. (2011). Why we hate performance management – And why we should love it? Journal of Business Horizons, 54(6), 503-507. https://doi.org/10.1016/j.bushor.2011.06.001

Altarawneh, I. I. (2016). Strategic human resources management and its impact on performance: the case from Saudi Arabia. International Journal of Business Management and Economic Research, 7(1), 486-503.

Armstrong, M. (2000). Performance management: Key strategies and practical guidelines. London, UK: Kogan Page Limited.

Arnaboldi, M., Lapsley, I., & Steccolini, I. (2015). Performance management in the public sector: The ultimate challenge. Journal of Financial Accountability and Management, 32(1), 1-22. https://doi.org/10.1111/faam.12049

Atanassov, K. (1983). Intuitionistic fuzzy sets, VII ITKR᾽s session. Sofia (Deposed in Central Science-Technical Library of Bulgarian Academy of Sciences 1697/84) (in Bulgarian).

Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), 87-96. https://doi.org/10.1016/S0165-0114(86)80034-3

Bach, S. (2005). New directions in performance management (Chapter 11). In S. Bach (Ed.), Managing human resources: personnel management in transition. Oxford: Blackwell.

Balin, A., & Baraçli, H. (2015). A fuzzy multi-criteria decision making methodology based upon the interval type-2 fuzzy sets for evaluating renewable energy alternatives in Turkey. Technological and Economic Development of Economy, 1-22. https://doi.org/10.3846/20294913.2015.1056276

Boswell, W. R. (2006). Aligning employees with the organization’s strategic objectives: Out of “line of sight”, out of mind. International Journal of Human Resource Management, 17(9), 1489-1511. https://doi.org/10.1080/09585190600878071

Boswell, W. R., Bingham, J. B., & Colvin, A. J. S. (2006). Aligning employees through “line of sight”. Business Horizons, 49(6), 499-509. https://doi.org/10.1016/j.bushor.2006.05.001

Bouskila-Yam, O., & Kluger, A. N. (2011). Strength-based performance appraisal and goal setting. Human Resource Management Review, 21(2), 137-147. https://doi.org/10.1016/j.hrmr.2010.09.001

Buller, P. F., & McEnvoy, G. M. (2012). Strategy, human resources management and performance: Sharpening line of sight. Human Resource Management Review, 22(1), 43-56. https://doi.org/10.1016/j.hrmr.2011.11.002

Cardy, R. L., & Leonard, B. (2011). Performance management: concepts, skills and exercises (2nd ed.). Armonk, NY: M. E. Sharpe.

Chadwick, C. (2010). Theoretic insights on the nature of performance synergies in human resource systems: Toward greater precision. Human Resource Management Review, 20(2), 85-101. https://doi.org/10.1016/j.hrmr.2009.06.001

Chen, T. Y. (2014). A prioritized aggregation operator-based approach to multiple criteria decision making using interval-valued intuitionistic fuzzy sets: A comparative perspective. Information Sciences, 281, 97-112. https://doi.org/10.1016/j.ins.2014.05.018

Chen, T. Y. (2017). Multiple criteria decision analysis using prioritised interval type-2 fuzzy aggregation operators and its application to site selection. Technological and Economic Development of Economy, 23(1), 1-21. https://doi.org/10.3846/20294913.2016.1209249

Chytas, P., Glykas, M., & Valiris, G. (2011). A proactive balanced scorecard. International Journal of Information Management, 31, 460-468. https://doi.org/10.1016/j.ijinfomgt.2010.12.007

Datta, D. K., Guthrie, J. P., & Wright, P. M. (2005). Human resource management and labor productivity: Does industry matter? Academy of Management Journal, 48(1), 135-145. https://doi.org/10.5465/amj.2005.15993158

Erdogan, B. (2002). Antecedents and consequences of justice perceptions in performance appraisals. Human Resources Review, 12(4), 555-578. https://doi.org/10.1016/S1053-4822(02)00070-0

Gruman, J. A., & Saks, A. M. (2011). Performance management and employee engagement. Human Resource Management Review, 21(2), 123-136. https://doi.org/10.1016/j.hrmr.2010.09.004

Guest, D. E. (2011). Human resource management and performance: Still searching for some answers. Human Resource Management Journal, 21(1), 3-13. https://doi.org/10.1111/j.1748-8583.2010.00164.x

Hajiagha, S. H. R., Hashemi, S. S., & Zavadskas, E. K. (2013). A complex proportional assessment method for group decision making in an interval-valued intuitionistic fuzzy environment. Technological and Economic Development of Economy, 19(1), 22-37. https://doi.org/10.3846/20294913.2012.762953

Jiang, K., Lepak, D. P., Han, K., Hong, Y., Kim, A., & Winkler, A. L. (2012). Clarifying the construct of human resource systems: Relating human resource management to employee performance. Human Resource Management Review, 22(2), 73-85. https://doi.org/10.1016/j.hrmr.2011.11.005

Lepak, D. P., Liao, H., Chung, Y., & Harden, E. E. (2006). A conceptual review of human resource management systems in strategic human resource management research (Chapter 7). In J. J. Matocchio (Ed.), Research in personnel and human resource management (Vol. 25, p. 217-271). Greenwich, CT: JAI Press. https://doi.org/10.1016/S0742-7301(06)25006-0

Liu, P., Li, Y., & Antuchevičienė, J. (2016). Multi-criteria decision-making method based on intuitionistic trapezoidal fuzzy prioritised OWA operator. Technological and Economic Development of Economy, 22(3), 453-469. https://doi.org/10.3846/20294913.2016.1171262

Mone, E. M., & London, M. (2010). Employee engagement through effective performance management: A practical guide for managers. New York, NY: Routledge.

Moona, S. H., Scullenb, S. E., & Lathamc, G. P. (2016). Precarious curve ahead: The effects of forced distribution rating systems on job performance. Human Resource Management Review, 26(2), 166-179. https://doi.org/10.1016/j.hrmr.2015.12.002

Paauwe, J., & Boselie, P. (2005). HRM and performance: What next? Human Resource Management Journal, 15(4), 68-83. https://doi.org/10.1111/j.1748-8583.2005.tb00296.x

Prowse, P., & Prowse, J. (2009). The dilemma of performance appraisal. Measuring Business Excellence, 13(4), 69-77. https://doi.org/10.1108/13683040911006800

Taylor, J. (2014). Organizational Culture and the paradox of performance management. Journal of Public Performance and Management Review, 38(1), 7-22. https://doi.org/10.2753/PMR1530-9576380101

Wei, G., Zhao, X., & Wang, H. (2012). An approach to multiple attribute group decision making with interval intuitionistic trapezoidal fuzzy information. Technological and Economic Development of Economy, 18(2), 317-330. https://doi.org/10.3846/20294913.2012.676995

Xu, Z. S., & Da, Q. L. (2003). Possibility degree method for ranking interval numbers and its application. Journal of System Engineering, 18(1), 67-70.

Yang, W., Chen, Z., & Zhang, F. (2017). New group decision making method in intuitionistic fuzzy setting based on TOPSIS. Technological and Economic Development of Economy, 23(3), 441-461. https://doi.org/10.3846/20294913.2015.1072754

Youndt, M. A., Snell, S. A., Dean, J. W., & Lepak, D. P. (1996). Human resource management, manufacturing strategy, and firm performance. Academy of Management Journal, 39(4), 836-866.

Yu, D. (2013). Intuitionistic fuzzy prioritized operators and their application in multi-criteria group decision making. Technological and Economic Development of Economy, 19(1), 1-21. https://doi.org/10.3846/20294913.2012.762951

Zavadskas, E. K., Bausys, R., Kaklauskas, A., Ubartė, I., Kuzminskė, A., & Gudienė, N. (2017). Sustainable market valuation of buildings by the single-valued neutrosophic MAMVA method. Applied Soft Computing, 57, 74-87. https://doi.org/10.1016/j.asoc.2017.03.040

Zavadskas, E. K., Bausys, R., & Lazauskas, M. (2015). Sustainable assessment of alternative sites for the construction of a waste incineration plant by applying WASPAS method with single-valued neutrosophic set. Sustainability, 7(12), 15923-15936. https://doi.org/10.3390/su71215792

Zhao, H., Xu, Z., Ni, M., & Liu, S. (2010). Generalized aggregation operators for intuitionistic fuzzy sets. International Journal of Intelligent Systems, 25(1), 1-30. https://doi.org/10.1002/int.20386

Zhou, L., Tao, Z., Chen, H., & Liu, J. (2014). Continuous interval-valued intuitionistic fuzzy aggregation operators and their applications to group decision making. Applied Mathematical Modelling, 38(7-8), 2190-2205. https://doi.org/10.1016/j.apm.2013.10.036